School of Life Sciences, University of Sussex, Falmer, Brighton BN1 9QG, UK.
J Exp Biol. 2013 May 15;216(Pt 10):1766-70. doi: 10.1242/jeb.082941. Epub 2013 Jan 24.
Ants can use visual information to guide long idiosyncratic routes and accurately pinpoint locations in complex natural environments. It has often been assumed that the world knowledge of these foragers consists of multiple discrete views that are retrieved sequentially for breaking routes into sections controlling approaches to a goal. Here we challenge this idea using a model of visual navigation that does not store and use discrete views to replicate the results from paradigmatic experiments that have been taken as evidence that ants navigate using such discrete snapshots. Instead of sequentially retrieving views, the proposed architecture gathers information from all experienced views into a single memory network, and uses this network all along the route to determine the most familiar heading at a given location. This algorithm is consistent with the navigation of ants in both laboratory and natural environments, and provides a parsimonious solution to deal with visual information from multiple locations.
蚂蚁可以利用视觉信息来引导长而独特的路线,并在复杂的自然环境中准确地定位位置。人们通常认为,这些觅食者的世界知识由多个离散的视图组成,这些视图是按顺序检索的,以便将路线分成控制接近目标的部分。在这里,我们使用一种不存储和使用离散视图的视觉导航模型来挑战这个观点,该模型复制了被视为蚂蚁使用这种离散快照进行导航的典型实验的结果。该架构不是按顺序检索视图,而是将来自所有经验视图的信息汇集到一个单一的记忆网络中,并在整个路线上使用该网络来确定给定位置最熟悉的航向。该算法与蚂蚁在实验室和自然环境中的导航一致,并为处理来自多个位置的视觉信息提供了一个简洁的解决方案。